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Influence of meltwater from Labrador Sea ice and icebergs transported via the Flemish cap on the long-term North Atlantic cold anomaly
Get PDFThe long-term North Atlantic Cold Anomaly (Cold Blob, CB) was largely defined by three major episodes of low sea surface temperature (SST) in the subpolar North Atlantic in 1972–1974, 1984–1985 and 1991–1994. Without these cold periods, there would have been no CB. Each of these episodes correlated with unusually low SST at the Flemish Cap (a subsurface island of the Canadian continental shelf) and with periods of high sea ice cover over the deep basin of the Labrador Sea a year earlier. These cold periods at the Flemish Cap and the CB were associated with the advance of sea ice and icebergs to the Flemish Cap, high iceberg counts off the coast of Newfoundland and the encroachment of icebergs on the path of the North Atlantic Current (NAC). Studies of SST anomalies in high iceberg years provided evidence for surface connections between the Flemish Cap and the CB utilizing part of the NAC pathway. We propose that in the cold periods, residual meltwater from sea ice and icebergs conveyed in the Labrador Current to the Flemish Cap was relayed via the NAC to the subpolar North Atlantic to form the CB. After 1995, anomalous ice expansion in the Labrador Sea basin greatly diminished, sea ice and icebergs did not reach the Flemish Cap and cold meltwater was no longer transmitted to the subpolar North Atlantic to sustain the CB. These observations make it difficult to see how the CB could be relevant to mooted changes in the Atlantic Meridional Overturning Circulation and associated impacts on regional climate in the twenty-first century
Building and explaining data-driven energy demand models for Indian states
Get PDFAccurate forecasts of energy demand are crucial for managing India's rapidly growing energy needs as it continues to decarbonise its grid. In this study, we develop state-level data driven models to predict weather-driven energy demand across India using the eXtreme Gradient Boosting framework. The models use as input population-weighted meteorological variables averaged over various timescales. The models are trained on daily energy demand data, scraped from reports issued by Grid-India, which we correct for trends in population and economic growth. The models demonstrate high skill, with half having r² > 0.8, significantly outperforming traditional multivariate linear regression models. We explain model behaviour through Shapley analysis and find a strong sensitivity to day of the week and public holidays, with reductions in energy demand on Sundays and varying impacts during holidays. While important variables vary by state and season, daily minimum temperature and 30 d mean temperature consistently emerge as key predictors, reflecting nighttime air conditioning use and seasonal heating or cooling needs. We also identify threshold behaviours, indicating large increases in energy demand once temperatures pass certain values. Using reanalysis, we extend our models to estimate all-India energy demand from 1979–2023, calibrated to 2023 conditions. We confirm a pronounced seasonal cycle, with greatest demand during the pre-monsoon and monsoon onset (May–June) and lowest demand in the winter (November–December). Combining these results with timeseries of renewable energy production, we find the largest energy deficit (demand minus renewable generation) occurs during or after monsoon withdrawal (September–October). Extreme deficit days, posing a risk to the national grid, are associated with early monsoon withdrawal or late monsoon breaks, leading to low wind speeds and persistently high dewpoint temperatures and cloud cover. The demand dataset created here can be used for energy grid management, siting of future renewable energy generation, and to aid with ensuring security of supply
The Convention on Nuclear Safety for Nuclear Power Plants: Between Stability and Reform during a Quarter Century
No full textConsidering the importance of protecting people and the environment against
the dangers arising from ionising radiation from nuclear installations, this research
project focuses on the Convention on Nuclear Safety applicable to nuclear power
plants, adopted in 1994 and entered into force in 1996. The research question explores
the Convention’s positioning between stability and reform, with the aid of a new model
whose application can be extended to other treaties. To support the answer to the
research question, the thesis proposes a new theoretical approach associated with the
legal analysis, which regards the Convention as a ‘formal institution’ and applies a
set of historical institutionalist concepts as an explanatory device for its evolution. The
research project studies the Convention’s formation, and its development over 25 years
since its entry into force (1996 - 2021), over a three-phase chronology. It finds that the
Treaty’s institutional architecture, designed in the aftermath of the 1986 first major
nuclear accident at Chernobyl (an exogenous shock classified at the highest severity
level), was the root cause for the Convention’s enduring path dependence. The Treaty
has remained unaffected, even when a reform could have occurred, notably in the
aftermath of the 2011 second major nuclear accident in history at Fukushima (ranked
at the highest severity level). Instead of undergoing a reform of the core Treaty (which
would have entailed important efforts in terms of time, costs, and procedures), new
developments arising from significant exogenous nuclear events and from the
Convention’s implementation monitoring have been gradually absorbed into auxiliary
legal instruments and processes (procedural arrangements and peer-review process,
declaration, standards). These are referred to in the thesis as ‘institutional
mechanisms’ supporting the Convention’s implementation. The research proposes the
new concept of the ‘institutional system of the Convention’, composed of the formal
institution and the institutional mechanisms. It finds that the Convention’s stability
was ensured through the coexistence of the path dependence of the Treaty as a formal
institution with the compensatory dynamic actualisations of the institutional
mechanisms. This formula has also ensured the institutional system’s adaptability.
Based on the Convention’s case study, the thesis proposes, as a novelty, a hybrid legal
– historical institutionalist model that can be used to study the evolution of other
international treaties in different areas, also supporting future decisions on their
development. Thereby, the thesis contributes to the international nuclear law
literature and the historical institutionalism literature
Quantifying the ozone radiative feedback on planetary-wave and zonal-mean variability during the Southern Hemisphere stratospheric polar vortex breakdown
Get PDFStratospheric ozone has been shown to impact stratospheric variability and subseasonal-to-seasonal (S2S) prediction via its strong radiative properties. Previous research investigating the impact of interactive ozone in atmospheric models, compared with the use of a prescribed climatology, has focused largely on the zonal-mean impacts. Here, we employ a process-based diagnostic to quantify the impact of interactive ozone on high-latitude stratospheric variability in the Southern Hemisphere during the vortex breakdown period using two seasonal hindcast ensembles (one with and one without interactive ozone) initialised on October 1st over a period of 29 years. We focus on the amplitudes of waves (i.e., the longitudinal deviations from the zonal mean) and of zonal-mean deviations from the ensemble mean, for both temperatures and zonal winds. The effect is quantified as a function of day of year, considering the strong non-stationarity during this season, and we focus on the lower stratosphere, a region crucial for stratosphere-troposphere coupling. For both the waves and the zonal mean, we show that interactive ozone provides a positive radiative feedback on the variability. This increases the variances of both the waves and the zonal-mean deviations. Also, the ozone-temperature correlations are strengthened. The feedback acts most strongly on zonal wavenumbers 1 and 2. Interactive ozone is found to increase the predictable signal of the final warming date, bringing it closer to reanalysis, even though the anomaly correlation coefficient is reduced. This reflects the limitations of the anomaly correlation coefficient as a metric of skill in the presence of a signal deficit
Nexus between solar-PV adoption and wild food sustainability: case of income from honey, fruits, traditional-beer, and vegetables in rural Zambia
Get PDFRural Zambia faces critical energy access challenges, with electrification rates below 15 % and over 12 million people lacking electricity. The reliance on hydroelectric power, exacerbated by climate-induced droughts, has led to severe energy shortages and up to 21-hour daily load-shedding. This research addresses the dual challenge of energy poverty and unsustainable edible non-timber forest product (ENTFP) practices in rural Zambia. Despite the potential of solar photovoltaic (PV) systems to mitigate energy poverty and enhance livelihoods, adoption remains limited. Simultaneously, wild foods - such as wild honey, fruits, traditional beer, and leafy vegetables - are not only consumed in rural areas, but also crucial income sources. However, they face unsustainable harvesting practices, threatening rural food security, biodiversity and long-term viability. This study investigated the relationship between ENTFP - derived income and solar PV adoption. It explored financing mechanisms tied to ENTFPs, evaluated their benefits and limitations, and examined their environmental and social impacts. The study utilized the Rural Development Stakeholder Hybrid Adoption Model (RUDSHAM), integrating theories such as Technology Acceptance Model, Diffusion of Innovations, and Social Learning Theory. Data were collected
through 40 in-depth interviews, 7 focus group discussions, and stakeholder consultations across three rural districts in Zambia. NVIVO 14 was employed for thematic coding and analysis, ensuring representation of diverse stakeholder perspectives. Income from ENTFPs supports solar PV adoption by providing critical financial resources. Some ENTFPs like wild honey sometimes yield even higher revenues than agriculture, enabling energy investments. However, commercialization poses food security and sustainability risks, such as habitat degradation and resource depletion. Social impacts include empowerment through improved energy access but also risks of community conflict over resource competition. Solar PV systems contribute to reduced deforestation and CO2 emissions, aligning with environmental conservation goals, but require balanced management of ENTFP
practices to ensure ecological health. The study recommends the need for robust policies promoting sustainable ENTFP harvesting and solar PV integration. Community-driven strategies, coupled with educational initiatives on sustainable practices, can promote resilience and energy equity. Expanding alternative income sources can mitigate overdependence on ENTFPs, ensuring balanced economic, social, and environmental outcomes
The impact of noise on green open space value
Get PDFI investigate the effect of noise on the amenity value of urban green open spaces in Prague, Czech Republic. First, I use standard hedonic pricing model exploiting cross-sectional and quasi-experimental variation in the apartment price data and then I analyse green open spaces quality inferred from a quantitative spatial model. Results show that increasing size of quiet green open spaces (with noise below 60 dB) by 10% increases local apartment prices by 0.05% and perceived quality of green open spaces by 1.2%. In a counterfactual scenario, if noise in green open spaces decreases by 2 dB, a noise reduction achieved by implementing 30 km/h speed limit in a city, value of apartments would increase by 0.2% due to increased size of accessible quiet green open spaces
Inter-platelet communication driving thrombus formation is regulated by extracellular calpain-1 cleavage of connexin 62
No full textConnexin (Cx) gap junction proteins are expressed by a multitude of cells and function as plasma membrane hemichannels or dock to form intercellular communication tunnels. Whilst Cx43 has garnered considerable attention, less is known about the structure and function of Cx62 channels. Platelets and megakaryocytes express Cx37, Cx40 and Cx62, which contribute to hemostatic and thrombotic responses. Our study explores an unexpected finding that following platelet activation, an extracellular region of Cx62 undergoes proteolytic cleavage by calpain-1. We adopted an interdisciplinary approach to evaluate structural and functional consequences of calpain-mediated cleavage of Cx62. Cellular signaling was assayed by immunoblotting, aggregation and calcium flux assays. Gap junction function and thrombus formation were assessed under arteriolar flow. In silico modelling was used to predict calpain-mediated changes to the pore diameter and design a decoy peptide (62Pept-NT). Mechanistically, Cx62 cleavage is Ca2+-dependent and requires calpain-1 externalization. Modelling a predicted calpain-1 cleavage site on the first extracellular loop, shows that calpain can dock to Cx62 monomers, promoting stepwise channel cleavage. Consequently, we predict a significant pore dilation enhancing diffusion of signaling molecules between cells and into the extracellular milieu. We designed a decoy peptide that abrogated calpain-1-mediated cleavage, reduced intercellular communication and restricted thrombus growth. Cx62 cleavage was dependent upon sequential action of protein kinase A, protein phosphatase 2A and Ca2+ release from intracellular stores. Extracellular calpain cleavage represents a fundamentally new regulatory mechanism for connexin 62, culminating in an irreversible open state
A comparison of volcanic ash source term characteristics estimated by source inversion and plume rise modelling methods: Raikoke 2019
Get PDFPredictions of volcanic ash location and concentration following an eruption rely heavily on estimates of source term characteristics including mass eruption rate, vertical distribution of ash and particle size distribution. These
characteristics can be provided by several methods including (i) preset values based on historical data, (ii) near-source plume rise model simulations, (iii) a combination of satellite retrievals and long-range dispersion model simulations(known as source inversion).
For the first time, this study presents a comparison of source term characteristics from these different methods.
The study focuses on the 2019 Raikoke eruption and analysis of the volcanic ash cloud 150 km downwind from the volcano vent, representing an effective source term for the dispersion of ash in the distal volcanic cloud. Results indicate good agreement in the vertical distribution of ash between the plume rise and source inversion methods but large differences in estimates of the horizontal mass flux at this distance. The plume rise model demonstrates the rapid sedimentation and deposition of coarse (> 100μm
diameter) ash particles close to the volcano vent resulting in a particle size distribution comparable to the preset distribution used operationally by the London VAAC at this range. These results suggest that source inversion can
provide a computationally cheaper alternative to the 3D plume rise method for estimating the vertical distribution of ash, and that the assumption of near-source fallout of coarse particles in the preset particle size distribution
holds fairly well. Further investigations are recommended including particle aggregation effects to understand differences in estimates of the effective
mass eruption rate
The ensemble transform Schmidt-Kalman filter: a novel method to compensate for observation uncertainty due to unresolved scales
Get PDFData assimilation is a mathematical technique that uses observations to improve model predictions through consideration of their respective uncertainties. Observation
error due to unresolved scales occurs when there is a difference in scales observed and modelled. To obtain an optimal estimate through data assimilation, the error due to
unresolved scales must be accounted for in the algorithm. In this work, we derive a novel ensemble transform formulation of the Schmidt-Kalman filter (ETSKF) to compensate for observation uncertainty due to unresolved scales in nonlinear dynamical systems. The ETSKF represents the small-scale variability through an ensemble sampled from
the representation error covariance. This small-scale ensemble is added to the largescale forecast ensemble to obtain an ensemble representative of all scales resolved by
the observations. We illustrate our new method using a simple nonlinear system of ordinary differential equations with two timescales known as the swinging spring (or
elastic pendulum). In this simple system, our novel method performs similarly to another method of compensating for uncertainty due to unresolved scales. Indeed, use of small-scale ensemble statistics has potential as a new approach to compensate for uncertainty due to unresolved scales in nonlinear dynamical systems but will need further testing
using more complicated systems